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library(plotly)

Attaching package: ‘plotly’

The following object is masked from ‘package:ggplot2’:

    last_plot

The following object is masked from ‘package:stats’:

    filter

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    layout

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names(df)

 [1] "Release"               "Release.date"          "Release.type"          "Band"                  "Genre"                
 [6] "Location"              "Lyrical.themes"        "Number.of.reviews"     "Average.rating"        "genre_early"          
[11] "genre_later"           "genre_early_secondary" "genre_later_secondary" "location_early"        "genre_early_main"     
[16] "genre_later_main"      "genre_early_stripped"  "genre_later_stripped" 

levels(df_year$genre_early_main)

 [1] "Heavy Metal"       "Doom Metal"        "Thrash Metal"      "Power Metal"       "Nu Metal"          "Progressive Metal"
 [7] "Black Metal"       "Metalcore"         "Death Metal"       "Folk Metal"        "Ambient"          

g1 <- ggplot(df_year, aes(x=release_year, y=percent, fill=fct_rev(genre_early_main))) + 
    geom_area(position = 'stack') + 
  labs(x="Release Year", 
       y = "Percent of Releases", 
       fill = "Main Genre",
       title = "Percent of Metal Genre Releases By Year") + 
  #xlim(c(1970, 2018)) + ylim(c(0, 1)) + 
    scale_y_continuous(limits=c(0,1), labels = scales::percent, expand = c(0, 0)) + 
  scale_x_continuous(limits=c(1970, 2018), expand = c(0, 0)) + 
  scale_fill_manual(values = c("Black Metal" = "#000000", #black
                                "Death Metal" = "#8f0000", #dark red
                               "Thrash Metal" = "#7cf000", #light green
                               "Doom Metal" = "#7e3f0c", #brown
                               "Ambient" = "#7d7d7d", #gray
                               "Power Metal" = "#f72bad", #pink
                               "Heavy Metal" = "#1d00fa", #blue
                               "Metalcore" = "#ee6917",
                               "Nu Metal" = "#ffd60a",
                               "Progressive Metal" = "#0adeff", #light blue
                               "Folk Metal" = "#b120d9" #purple
                               )
                     ) + 
  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
  panel.background = element_blank(), axis.line = element_line(colour = "black"))
ggplotly(g1)

df %>% filter(!(genre_early_main %in% c('Rock', 'Other'))) %>%
  mutate(release_year = as.numeric(str_sub(Release.date, 1, 4))) %>% 
  filter(Number.of.reviews >= 5) %>%
  ggplot() + 
  geom_point(aes(x = Number.of.reviews, 
                 y = Average.rating,
                 color = genre_early_main), 
             position = position_jitter(width = 0.5, height = 0.5),
             size = 0.7) + 
  labs(x="Number of Reviews", 
       y = "Rating", 
       color = "Main Genre",
       title = "Metal Releases By Rating and Number of Reviews") + 
    scale_color_manual(values = c("Black Metal" = "#000000", #black
                                "Death Metal" = "#8f0000", #dark red
                               "Thrash Metal" = "#7cf000", #light green
                               "Doom Metal" = "#7e3f0c", #brown
                               "Ambient" = "#7d7d7d", #gray
                               "Power Metal" = "#f72bad", #pink
                               "Heavy Metal" = "#1d00fa", #blue
                               "Metalcore" = "#ee6917",
                               "Nu Metal" = "#ffd60a",
                               "Progressive Metal" = "#0adeff", #light blue
                               "Folk Metal" = "#b120d9" #purple
                               )
                     ) + 
    scale_y_continuous(limits=c(0,100),  expand = c(0, 0)) + 
  scale_x_continuous(limits=c(5, 45), expand = c(0, 0)) + 
  theme_light() + 
  theme(#panel.grid.major = element_blank(), 
        #panel.grid.minor = element_blank(),
        #panel.background = element_blank(), 
        axis.line = element_line(colour = "black"))

  #geom_jitter()